41 citations · 134 across the 14 of their papers we have counts for
9 papers · 1 filter
Improved Cross-Lingual Transfer Learning For Automatic Speech Translation
Sameer Khurana, Nauman Dawalatabad, Antoine Laurent +4
Research in multilingual speech-to-text translation is topical. Having a single model that supports multiple translation tasks is desirable. The goal of this work it to improve cro…
ASR-Generated Text for Language Model Pre-training Applied to Speech Tasks
Valentin Pelloin, Franck Dary, Nicolas Herve +4
We aim at improving spoken language modeling (LM) using very large amount of automatically transcribed speech. We leverage the INA (French National Audiovisual Institute) collectio…
SAMU-XLSR: Semantically-Aligned Multimodal Utterance-level Cross-Lingual Speech Representation
Sameer Khurana, Antoine Laurent, James Glass
We propose the SAMU-XLSR: Semantically-Aligned Multimodal Utterance-level Cross-Lingual Speech Representation learning framework. Unlike previous works on speech representation lea…
ON-TRAC Consortium Systems for the IWSLT 2022 Dialect and Low-resource Speech Translation Tasks
Marcely Zanon Boito, John Ortega, Hugo Riguidel +8
This paper describes the ON-TRAC Consortium translation systems developed for two challenge tracks featured in the Evaluation Campaign of IWSLT 2022: low-resource and dialect speec…
Magic dust for cross-lingual adaptation of monolingual wav2vec-2.0
Sameer Khurana, Antoine Laurent, James Glass
We propose a simple and effective cross-lingual transfer learning method to adapt monolingual wav2vec-2.0 models for Automatic Speech Recognition (ASR) in resource-scarce languages…
End2End Acoustic to Semantic Transduction
Valentin Pelloin, Nathalie Camelin, Antoine Laurent +4
In this paper, we propose a novel end-to-end sequence-to-sequence spoken language understanding model using an attention mechanism. It reliably selects contextual acoustic features…
Recent Advances in End-to-End Spoken Language Understanding
Natalia Tomashenko, Antoine Caubriere, Yannick Esteve +2
This work investigates spoken language understanding (SLU) systems in the scenario when the semantic information is extracted directly from the speech signal by means of a single e…
Curriculum-based transfer learning for an effective end-to-end spoken language understanding and domain portability
Antoine Caubrière, Natalia Tomashenko, Antoine Laurent +3
We present an end-to-end approach to extract semantic concepts directly from the speech audio signal. To overcome the lack of data available for this spoken language understanding…
End-to-end named entity extraction from speech
Sahar Ghannay, Antoine Caubrière, Yannick Estève +2
Named entity recognition (NER) is among SLU tasks that usually extract semantic information from textual documents. Until now, NER from speech is made through a pipeline process th…